• Communications for Statistical Applications and Methods
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• v.16 no.4
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• pp.595-603
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• 2009

Typically the standard optimal allocation method distributes the sample for each stratum considering survey cost. In case of varying survey cost for each survey unit, we need to consider more practical allocation method. In other words, according to characteristics of an individual unit, we consider the optimal dynamic allocation method which first selects the survey unit having maximum value of benefit cost ratio. In terms of this, the proposed allocation method is different from standard optimal allocation method which allocate samples for each stratum and selects the random sample according to each size of sample. This paper is considered the dynamic optimal allocation method for the stratified randomized response technique which surveys for sensitive characteristic of survey units such as drug abuse, abortion, alcoholic. We prove the practical usefulness of proposed method using the numerical example.

• The Korean Journal of Applied Statistics
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• v.31 no.5
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• pp.587-597
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• 2018

Procedures, such as sampling technique, survey method, and questionnaire preparation, are required in order to obtain sample data in accordance with the purpose of a survey. An important procedure is the decision of the sample size formula. The sample size formula is determined by setting the target error and total cost according to the sampling method. In this paper, we propose a sample size formula using population changes over time, estimation error of the previous time and response rate of past data when the target error and the expected response rate are given in the simple random sampling. In actual research, we use estimators that apply complex weights in addition to design-based weights. Therefore, we induce a sample size formula for estimators using design-based weights and nonresponse adjustment coefficients, that can be a formula that reflects differences in response rates when survey methods are changed over time. In addition, we use simulations to compare the proposed formula with the existing sample size formula.

• Communications for Statistical Applications and Methods
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• v.11 no.2
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• pp.297-311
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• 2004

In the sample survey for a highly skewed population, stratum jumpers often occur. Stratum jumpers are units having large discrepancies between a stratification variable and a study variable. We propose two models for stratum jumpers: a multiplicative model and a random replacement model. We also consider the modification of the L-H stratification algorithm such that we apply the previous models to L-H algorithm in determination of the sample sizes and the stratum boundaries. We evaluate the performances of the new stratification algorithms using real data. The result shows that L-H algorithm for the random replacement model outperforms other algorithms since the estimator has the least coefficient of variation.

• Communications for Statistical Applications and Methods
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• v.11 no.2
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• pp.399-411
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• 2004

A common method of handling nonresponse in sample survey is to delete the cases, which may result in a substantial loss of cases. Thus in certain situation, it is of interest to create a complete set of sample values. In this case, a popular approach is to impute the missing values in the sample by the mean or the median of responders. The difficulty with this method which just replaces each missing value with a single imputed value is that inferences based on the completed dataset underestimate the precision of the inferential procedure. Various suggestions have been made to overcome the difficulty but they might not be appropriate for public-use files where the user has only limited information for about the reasons for nonresponse. In this note, a multiple imputation method is considered to create complete dataset which might be used for all possible inferential procedures without misleading or underestimating the precision.

• Communications for Statistical Applications and Methods
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• v.16 no.6
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• pp.1031-1036
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• 2009

Under recent dramatic declines in response rates, various procedures have been considered among survey practitioners to reduce nonresponse in order to avoid its potential impairment to the inference. In the random digit dialing telephone surveys, substantial efforts are often required to obtain the initial contact for the screener interview. To reduce a burden with higher data collection costs, refusal conversion can be administered only to a random portion of the sample, reducing nonresponse (bias) with an expense of sample variability increment due to the associated weight adjustment. In this paper, we provide ways to determine the optimal subsampling rate using a linear cost model. Our approach for refusal subsampling is to predetermine a random portion from the full sample and to apply refusal conversion efforts if needed only to the subsample.

• Survey Research
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• v.11 no.1
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• pp.19-41
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• 2010

Although it is possible to provide statistically reliable estimators of the entire population parameters based on each independent rolling sample, estimators of the small areas may not have the required statistical efficiency. Thus, in general, small area estimators are calculated based on the combined rolling sample after entire rolling sample survey is finished. In this study, we considered the construction of weights that is necessary in the analysis of the combined rolling sample. Unlike the past studies that provided the empirical results for the corresponding specific rolling sample survey, we considered linear models that depends only on design variables and rolling period and provided the corresponding Best Linear Unbiased Predictor(BLUP). Through a simulation study, we proposed the estimators for the population parameters that are robust to model failure and the BLUP under the assumed model. The results are applied to the 4th Korea National Health and Nutrition Examination Survey.

• The Korean Journal of Applied Statistics
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• v.10 no.2
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• pp.215-226
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• 1997

The purpose of the labor statistics survey is to collect materials on employment, wages and the working time and to analyze the trend of the labor situation. in this research, the stratification variables are industry and the size of establishment. The sample are selected by stratified one stage sampling method in order to produce the reliable estimates of labor statistics. For local labor statistics, we design the sample survey using the city and province as sub-population. So we are able to produce the local area estimates of labor statistics with respect to industry and the size of establishment.

• Communications for Statistical Applications and Methods
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• v.26 no.5
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• pp.507-517
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• 2019

Statistical matching is a method of combining multiple sources of data that are extracted or surveyed from the same population. It can be used in situation when variables of interest are not jointly observed. It is a low-cost way to expect high-effects in terms of being able to create synthetic data using existing sources. In this paper, we propose the several statistical micro matching methods using a multinomial logistic regression model when all variables of interest are categorical or categorized ones, which is common in sample survey. Under conditional independence assumption (CIA), a mixed statistical matching method, which is useful when auxiliary information is not available, is proposed. We also propose a statistical matching method with auxiliary information that reduces the bias of the conventional matching methods suggested under CIA. Through a simulation study, proposed micro matching methods and conventional ones are compared. Simulation study shows that suggested matching methods outperform the existing ones especially when CIA does not hold.

• Survey Research
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• v.5 no.1
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• pp.103-130
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• 2004

Main monthly household surveys conducted by Korea National Statistical Office are economically active population survey(EAPS) and household income and expenditure survey(HIES). Samples of these two surveys are redesigned every 5 years based on Census. This paper is about sample redesign of household survey conducted in 2002 based on 2000 Census. Main improvements of 2002 sample redesign are the introduction of rotation sampling system, the expansion of HIES survey area from urban to whole country and the foundation of basement to make small area estimation for the unemployment statistics. Also the number of sample households within a enumeration district(ED) is reduced from 24 to 20. That makes it possible to select more ED samples which provides better precision for EAPS and HIES. To select representative samples for the population, different classification index is used for each metropolitan area and provinces.

• Proceedings of the Korean Statistical Society Conference
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• 2000.11a
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• pp.97-104
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• 2000

Time-related underemployment exists when a person's employment is insufficient in terms of the volume of work. Two alternative definitions can be considered based on a longer-term view or a shorter-term view and these were designed into a single questionnaire. We conducted a pilot sample survey with about 6,000 respondents in Korea. The estimates of underemployment using the two definitions show some differences given the ages, genders, industrial areas and main activities of the respondents. A larger number of people could be identified as underemployed when the longer-term view is used than when the shorter-term view is used, but there is a greater cost associated with the former. The cost-benefit of the interviewers' time was investigated by multiple visits to households. Biases and costs are also analyzed using the results of the comparison of the decrease in non-responses with the increase in the costs for the interviews.